remove hf_access_token cli arg
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2724f00752
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4
train.py
4
train.py
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@ -432,8 +432,7 @@ def main(args):
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try:
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# first try to download from HF
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model_root_folder = try_download_model_from_hf(repo_id=args.resume_ckpt,
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subfolder=args.hf_repo_subfolder,
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access_token=args.hf_access_token)
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subfolder=args.hf_repo_subfolder)
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# if that doesn't work, try a local folder
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if model_root_folder is None:
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model_root_folder = convert_to_hf(args.resume_ckpt)
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@ -887,7 +886,6 @@ if __name__ == "__main__":
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argparser.add_argument("--gpuid", type=int, default=0, help="id of gpu to use for training, (def: 0) (ex: 1 to use GPU_ID 1)")
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argparser.add_argument("--gradient_checkpointing", action="store_true", default=False, help="enable gradient checkpointing to reduce VRAM use, may reduce performance (def: False)")
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argparser.add_argument("--grad_accum", type=int, default=1, help="Gradient accumulation factor (def: 1), (ex, 2)")
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argparser.add_argument("--hf_access_token", type=str, default=None, help="Huggingface.co access token")
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argparser.add_argument("--hf_repo_subfolder", type=str, default=None, help="Subfolder inside the huggingface repo to download, if the model is not in the root of the repo.")
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argparser.add_argument("--logdir", type=str, default="logs", help="folder to save logs to (def: logs)")
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argparser.add_argument("--log_step", type=int, default=25, help="How often to log training stats, def: 25, recommend default!")
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